Artificial intelligence applied to image-guided radiation therapy (IGRT): a systematic review by the Young Group of the Italian Association of Radiotherapy and Clinical …
L Boldrini, A D'Aviero, F De Felice, I Desideri… - La radiologia …, 2024 - Springer
Introduction The advent of image-guided radiation therapy (IGRT) has recently changed the
workflow of radiation treatments by ensuring highly collimated treatments. Artificial …
workflow of radiation treatments by ensuring highly collimated treatments. Artificial …
Movienet: Deep space–time‐coil reconstruction network without k‐space data consistency for fast motion‐resolved 4D MRI
Purpose To develop a novel deep learning approach for 4D‐MRI reconstruction, named
Movienet, which exploits space–time‐coil correlations and motion preservation instead of k …
Movienet, which exploits space–time‐coil correlations and motion preservation instead of k …
Modeling of artificial intelligence-based respiratory motion prediction in MRI-guided radiotherapy: a review
The advancement of precision radiotherapy techniques, such as volumetric modulated arc
therapy (VMAT), stereotactic body radiotherapy (SBRT), and particle therapy, highlights the …
therapy (VMAT), stereotactic body radiotherapy (SBRT), and particle therapy, highlights the …
Modeling linear accelerator (Linac) beam data by implicit neural representation learning for commissioning and quality assurance applications
Abstract Background Linear accelerator (Linac) beam data commissioning and quality
assurance (QA) play a vital role in accurate radiation treatment delivery and entail a large …
assurance (QA) play a vital role in accurate radiation treatment delivery and entail a large …
Training deep learning based dynamic MR image reconstruction using open-source natural videos
To develop and assess a deep learning (DL) pipeline to learn dynamic MR image
reconstruction from publicly available natural videos (Inter4K). Learning was performed for a …
reconstruction from publicly available natural videos (Inter4K). Learning was performed for a …
Cancer Informatics for Cancer Centers: Sharing Ideas on How to Build an Artificial Intelligence–Ready Informatics Ecosystem for Radiation Oncology
In August 2022, the Cancer Informatics for Cancer Centers brought together cancer
informatics leaders for its biannual symposium, Precision Medicine Applications in Radiation …
informatics leaders for its biannual symposium, Precision Medicine Applications in Radiation …
Artificial intelligence‐based motion tracking in cancer radiotherapy: A review
Radiotherapy aims to deliver a prescribed dose to the tumor while sparing neighboring
organs at risk (OARs). Increasingly complex treatment techniques such as volumetric …
organs at risk (OARs). Increasingly complex treatment techniques such as volumetric …
Volumetric MRI with sparse sampling for MR‐guided 3D motion tracking via sparse prior‐augmented implicit neural representation learning
Background Volumetric reconstruction of magnetic resonance imaging (MRI) from sparse
samples is desirable for 3D motion tracking and promises to improve magnetic resonance …
samples is desirable for 3D motion tracking and promises to improve magnetic resonance …
Neural signals-based respiratory motion tracking: a proof-of-concept study
X Zhang, W Liu, F Xu, W He, Y Song, G Li… - Physics in Medicine …, 2023 - iopscience.iop.org
Objective. Respiratory motion tracking techniques can provide optimal treatment accuracy
for thoracoabdominal radiotherapy and robotic surgery. However, conventional imaging …
for thoracoabdominal radiotherapy and robotic surgery. However, conventional imaging …
Knowledge-Informed Machine Learning for Cancer Diagnosis and Prognosis: A review
Cancer remains one of the most challenging diseases to treat in the medical field. Machine
learning has enabled in-depth analysis of rich multi-omics profiles and medical imaging for …
learning has enabled in-depth analysis of rich multi-omics profiles and medical imaging for …